{"id":"https://openalex.org/W2030290736","doi":"https://doi.org/10.1145/1015330.1015382","title":"Learning to learn with the informative vector machine","display_name":"Learning to learn with the informative vector machine","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2030290736","doi":"https://doi.org/10.1145/1015330.1015382","mag":"2030290736"},"language":"en","primary_location":{"id":"doi:10.1145/1015330.1015382","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning - ICML '04","raw_type":"proceedings-article"},"type":"conference-abstract","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023849469","display_name":"Neil D. Lawrence","orcid":"https://orcid.org/0000-0001-9258-1030"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Neil D. Lawrence","raw_affiliation_strings":["University of Sheffield, Sheffield, U.K","[University of Sheffield, Sheffield, U.K]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sheffield, Sheffield, U.K","institution_ids":["https://openalex.org/I91136226"]},{"raw_affiliation_string":"[University of Sheffield, Sheffield, U.K]","institution_ids":["https://openalex.org/I91136226"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073032636","display_name":"John Platt","orcid":"https://orcid.org/0000-0002-5652-5303"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John C. Platt","raw_affiliation_strings":["Microsoft Research, Microsoft Corporation, Redmond, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Microsoft Research, Microsoft Corporation, Redmond, WA","institution_ids":["https://openalex.org/I1290206253"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":334,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"65","last_page":"65"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9793000221252441,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11236","display_name":"Control Systems and Identification","score":0.9726999998092651,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7985454797744751},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6909974813461304},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6593348979949951},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.6156943440437317},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6137460470199585},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5951550602912903},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5924612283706665},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5366076827049255},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5145580172538757},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37053853273391724},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.3656499981880188},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.26206594705581665}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7985454797744751},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6909974813461304},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6593348979949951},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.6156943440437317},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6137460470199585},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5951550602912903},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5924612283706665},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5366076827049255},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5145580172538757},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37053853273391724},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.3656499981880188},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26206594705581665},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/1015330.1015382","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015382","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning - ICML '04","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.2.4533","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.2.4533","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aicml.cs.ualberta.ca/banff04/icml/pages/papers/178.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.6700000166893005,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W174371023","https://openalex.org/W568924265","https://openalex.org/W1657213141","https://openalex.org/W2084812512","https://openalex.org/W2123152930","https://openalex.org/W2124158580","https://openalex.org/W2133013156","https://openalex.org/W2137956165","https://openalex.org/W2161767008","https://openalex.org/W2913340405","https://openalex.org/W3122943284"],"related_works":["https://openalex.org/W2090763504","https://openalex.org/W148178222","https://openalex.org/W2104657898","https://openalex.org/W1948992892","https://openalex.org/W1886884218","https://openalex.org/W1910826599","https://openalex.org/W2012353789","https://openalex.org/W1964286703","https://openalex.org/W2169866437","https://openalex.org/W3056417032"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"an":[3,84],"efficient":[4,36,79],"method":[5],"for":[6],"learning":[7,52],"the":[8,31,42,50,63,68,91],"parameters":[9,16],"of":[10],"a":[11,95],"Gaussian":[12],"process":[13],"(GP).":[14],"The":[15,54,71],"are":[17,23],"learned":[18],"from":[19,30,67],"multiple":[20],"tasks":[21],"which":[22],"assumed":[24],"to":[25,48,76],"have":[26],"been":[27],"drawn":[28],"independently":[29],"same":[32],"GP":[33],"prior.":[34],"An":[35],"algorithm":[37,47],"is":[38,73],"obtained":[39],"by":[40,60],"extending":[41],"informative":[43,65],"vector":[44],"machine":[45],"(IVM)":[46],"handle":[49],"multi-task":[51,55],"case.":[53],"IVM":[56,93],"(MTIVM)":[57],"saves":[58],"computation":[59],"greedily":[61],"selecting":[62],"most":[64],"examples":[66],"separate":[69],"tasks.":[70],"MT-IVM":[72],"also":[74],"shown":[75],"be":[77],"more":[78,88],"than":[80,90],"random":[81],"sub-sampling":[82],"on":[83],"artificial":[85],"data-set":[86],"and":[87],"effective":[89],"traditional":[92],"in":[94],"speaker":[96],"dependent":[97],"phoneme":[98],"recognition":[99],"task.":[100]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":21},{"year":2020,"cited_by_count":40},{"year":2019,"cited_by_count":18},{"year":2018,"cited_by_count":26},{"year":2017,"cited_by_count":21},{"year":2016,"cited_by_count":19},{"year":2015,"cited_by_count":14},{"year":2014,"cited_by_count":17},{"year":2013,"cited_by_count":17},{"year":2012,"cited_by_count":25}],"updated_date":"2026-07-19T07:52:34.831488","created_date":"2025-10-10T00:00:00"}
